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  2. Precision and recall - Wikipedia

    en.wikipedia.org/wiki/Precision_and_recall

    Precision and recall are then defined as: [12] = + = + Recall in this context is also referred to as the true positive rate or sensitivity, and precision is also referred to as positive predictive value (PPV); other related measures used in classification include true negative rate and accuracy. [12]

  3. Random sample consensus - Wikipedia

    en.wikipedia.org/wiki/Random_sample_consensus

    The threshold value to determine when a data point fits a model (t), and the number of inliers (data points fitted to the model within t) required to assert that the model fits well to data (d) are determined based on specific requirements of the application and the dataset, and possibly based on experimental evaluation.

  4. Threshold dose - Wikipedia

    en.wikipedia.org/wiki/Threshold_dose

    Threshold dose is the minimum dose of drug that triggers minimal detectable biological effect in an animal. [1] At extremely low doses, biological responses are absent for some of the drugs. The increase in dose above threshold dose induces an increase in the percentage of biological responses. [ 2 ]

  5. Receiver operating characteristic - Wikipedia

    en.wikipedia.org/wiki/Receiver_operating...

    A classification model (classifier or diagnosis [7]) is a mapping of instances between certain classes/groups.Because the classifier or diagnosis result can be an arbitrary real value (continuous output), the classifier boundary between classes must be determined by a threshold value (for instance, to determine whether a person has hypertension based on a blood pressure measure).

  6. Threshold model - Wikipedia

    en.wikipedia.org/wiki/Threshold_model

    The liability-threshold model is a threshold model of categorical (usually binary) outcomes in which a large number of variables are summed to yield an overall 'liability' score; the observed outcome is determined by whether the latent score is smaller or larger than the threshold. The liability-threshold model is frequently employed in ...

  7. Association rule learning - Wikipedia

    en.wikipedia.org/wiki/Association_rule_learning

    The Support Threshold is 30%, Confidence Threshold is 50%. The Table on the left is the original unorganized data and the table on the right is organized by the thresholds. In this case Item C is better than the thresholds for both Support and Confidence which is why it is first. Item A is second because its threshold values are spot on.

  8. Student's t-distribution - Wikipedia

    en.wikipedia.org/wiki/Student's_t-distribution

    2.2.2.2 ML variance estimate. ... The following table lists values for t ... 90% of the times that a lower threshold is calculated by this method from particular ...

  9. Activation function - Wikipedia

    en.wikipedia.org/wiki/Activation_function

    The binary step activation function is not differentiable at 0, and it differentiates to 0 for all other values, so gradient-based methods can make no progress with it. [ 7 ] These properties do not decisively influence performance, nor are they the only mathematical properties that may be useful.